Abstract not found

Dan Gottlieb provided critical data analysis using the Cooperative Cardiovascular Project. Financial support was provided by the National Institute on Aging. 1

We develop and implement a set of frameworks for valuing Medicaid coverage for recipients and apply them to welfare analysis of the Oregon Health Insurance Experiment, a Medicaid expansion that occurred via random assignment. Our baseline estimates of the welfare benefit to recipients from Medicaid per dollar of government spending range from about $0.2 to $0.4, depending on the framework, with a relatively robust lower bound of $0.2. At least two-fifths- and as much as four-fifths- of the value of Medicaid comes from a pure transfer component, as opposed to its ability to move resources across states of the world. In addition, we estimate that Medicaid generates a substantial transfer to non-recipients of about $0.6 per dollar of government spending. 1

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We survey the literature on social insurance, focusing on recent work that has connected theory to evidence to make quantitative statements about welfare and optimal policy. Our review contains two parts. We first discuss motives for government intervention in private insurance markets, focusing primarily on selection. We review the original theoretical arguments for government intervention in the presence of adverse selection, and describe how recent work has re ned and challenged the conclusions drawn from early theoretical models. We then describe empirical work that tests for selection in insurance markets, documents the welfare costs of this selection, and analyzes the welfare consequences of potential public policy interventions. In the second part of the paper, we review work on optimal social insurance policies. We discuss formulas for the optimal level of insurance benefits in terms of empirically estimable parameters. We then consider the consequences of relaxing the key assumptions underlying these formulas, e.g., by allowing for fiscal externalities or behavioral biases. We also summarize recent work on other dimensions of optimal policy, including mandated savings accounts and the optimal path of benefits. Finally, we discuss the key challenges that remain in understanding the optimal design of social insurance policies.

Retirement Research Consortium. The findings and conclusions expressed are solely

Regression discontinuity models, where the probability of treatment jumps discretely when a running variable crosses a threshold, are commonly used to nonparametrically identify and estimate a local average treatment effect. We show that the derivative of this treatment effect with respect to the running variable is nonparametrically identified and easily estimated. Then, given a local policy invariance assumption, we show that this derivative equals the change in the treatment effect that would result from a marginal change in the threshold, which we call the marginal threshold treatment effect (MTTE). We apply this result to Manacorda (2012), who estimates a treatment effect of grade retention on school outcomes. Our MTTE identifies how this treatment effect would change if the threshold for retention was raised or lowered, even though no such change in threshold is actually observed.

Any opinions expressed here are those of the author(s) and not those of IZA. Research published in this series may include views on policy, but the institute itself takes no institutional policy positions. The IZA research network is committed to the IZA Guiding Principles of Research Integrity. The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent nonprofit organization supported by Deutsche Post Foundation. The center is associated with the University of Bonn and offers a stimulating research environment through its international network, workshops and conferences, data service, project support, research visits and doctoral program. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author. IZA Discussion Paper No. 7622

Many empirical applications of regression discontinuity (RD) models use a running vari-able that is rounded and hence is discrete, e.g., age in years, or birth weight in ounces. This paper shows that standard RD estimation using a rounded discrete running variable leads to inconsistent estimates of treatment effects, even when the true functional form relating the outcome and the running variable is known and is correctly specied. This paper provides simple formulas to correct for this discretization bias. The proposed approach does not require instrumental variables, but instead uses information regarding the distribution of rounding er-rors, which is easily obtained and often close to uniform. The proposed approach is applied to estimate the effect of Medicare on insurance coverage in the US, and to investigate the retirement-consumption puzzle in China, utilizing the Chinese mandatory retirement policy.

and Their HealthThe Employment Policies Institute (EPI) is a nonprofit research organization dedicated to studying public policy issues surrounding employment growth. In particular, EPI research focuses on issues that affect entry-level employment. Among other issues, EPI research has quantified the impact of new labor costs on job creation, explored the connection between entry-level employment and welfare reform, and analyzed the demographic distribution of mandated benefits. EPI sponsors nonpartisan research that is conducted by independent economists at major universities around the country. Dr. June O’Neill is Wollman Distinguished Professor of Economics in the Wasserman Department of